Multi-Colony Ant Algorithm for Continuous Multi-Reservoir Operation Optimization Problem

Jalali, Mohammad Reza; Afshar, Abbas; Mariňo, Miguel A.

doi:10.1007/s11269-006-9092-5

Cited by 90 publications

(37 citation statements)

References 25 publications

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“…Therefore, discretization of original space may result in relatively poor performance of the ACO algorithms in continuous problems. Jalali et al (2007) employed the inherent potential of multi-colony ant system to tackle a continuous optimization problem. They utilized a multi-colony system with heterogeneous discretization scheme and possibility of information exchange between the colonies to provide a non-homogeneous and dynamic discretization scheme in the search space.…”

Section: Continuous Ant Colony Algorithms: Concepts and Mathematical mentioning

confidence: 99%

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An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems

Madadgar

Afshar

2008

Water Resour Manage

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Ant colony optimization was initially proposed for discrete search spaces while in continuous domains, discretization of the search space has been widely practiced. Attempts for direct extension of ant algorithms to continuous decision spaces are rapidly growing. This paper briefly reviews the central idea and mathematical representation of a recently proposed algorithm for continuous domains followed by further improvements in order to make the algorithm adaptive and more efficient in locating near optimal solutions. Performance of the proposed improved algorithm has been tested on few well-known benchmark problems as well as a real-world water resource optimization problem. The comparison of the results obtained by the present method with those of other ant-based algorithms emphasizes the robustness of the proposed algorithm in searching the continuous space more efficiently as locating the closest, among other ant methods, to the global optimal solution.

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Section: Continuous Ant Colony Algorithms: Concepts and Mathematical mentioning

confidence: 99%

“…In continuous domains, discretization of the search space has been successfully implemented. Jalali et al (2007) proposed a multi-colony ant algorithm to discretize the continuous search space non-homogenously in order to focus on the area surrounding the optimum solution.…”

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confidence: 99%

An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems

Madadgar

Afshar

2008

Water Resour Manage

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“…Otherwise, the one with smaller constraint violation value is selected. Overall, when any of the following conditions are met, (32) and the final effectiveness of e-constrained method strongly depends on the control method of ε value. Takahama et al [47] proposed the following method,…”

Section: Constraint Handlingmentioning

confidence: 99%

Long-Term Scheduling of Large-Scale Cascade Hydropower Stations Using Improved Differential Evolution Algorithm

Wen

Zhou

et al. 2018

Water

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Long-term scheduling of large cascade hydropower stations (LSLCHS) is a complex problem of high dimension, nonlinearity, coupling and complex constraint. In view of the above problem, we present an improved differential evolution (iLSHADE) algorithm based on LSHADE, a state-of-the-art evolutionary algorithm. iLSHADE uses new mutation strategies "current to pbest/2-rand" to obtain wider search range and accelerate convergence with the preventing individual repeated failure evolution (PIRFE) strategy. The handling of complicated constraints strategy of ε-constrained method is presented to handle outflow, water level and output constraints in the cascade reservoir operation. Numerical experiments of 10 benchmark functions have been done, showing that iLSHADE has stable convergence and high efficiency. Furthermore, we demonstrate the performance of the iLSHADE algorithm by comparing it with other improved differential evolution algorithms for LSLCHS in four large hydropower stations of the Jinsha River. With the applications of iLSHADE in reservoir operation, LSLCHS can obtain more power generation benefit than other alternatives in dry, normal, and wet years. The results of numerical experiments and case studies show that the iLSHADE has a distinct optimization effect and good stability, and it is a valid and reliable tool to solve LSLCHS problem.

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“…They emphasized superior performance of ACO, especially in longtime horizon operation models. Although ACO algorithms were originally proposed for discrete search spaces, it has successfully been applied to contiuous domains in water resources problems (Jalali et al 2007;Madadgar and Afshar 2009). In ACO algorithms, the optimization search procedure is made by the number of artificial ants.…”

Section: Ant Colony Optimization (Aco); An Overviewmentioning

confidence: 99%

Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm

Afshar

Masoumi

Solis

2015

Water Resour Manage

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Optimal design of irrigation and water supply reservoirs under reliability constraints may be categorized as large combinatorial optimization problems. In this paper, the reliability based optimum design of a single water supply reservoir is formulated as a mixed integer programming and a hybrid algorithm is introduced for its solution. To eliminate iterative procedures in reliability-based reservoir design and operation, the reliability requirements are directly embedded into the modeling framework and treated as different sets of constraints. Adaptive penalty method is used for constraint handling in the solution methodology. The proposed algorithm couples an ant colony optimization (ACO) optimizer with a virtual linear programing (LP) model for the solution of the resulted NP-hard mixed integer nonlinear programming problem. Dez reservoir for irrigation water supply with 480 months of inflow is used to demonstrate the method and its performance. The structure and solution methodology is verified by the solution to the inverse problem. It is shown that the proposed hybrid model can efficiently solve the problem for various combinations of reliability measures in a multiple period modeling scheme. It is illustrated that under some circumstances and specific reliability values, the mixed integer nonlinear programming (MINLP) solver may even fail to address a feasible and local optimal solution. Although operating rule is not included in the operational scheme, the procedure is capable of identifying coefficients for decision rules with any proposed structure.

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Multi-Colony Ant Algorithm for Continuous Multi-Reservoir Operation Optimization Problem

Cited by 90 publications

References 25 publications

An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems

An Improved Continuous Ant Algorithm for Optimization of Water Resources Problems

Long-Term Scheduling of Large-Scale Cascade Hydropower Stations Using Improved Differential Evolution Algorithm

Reliability Based Optimum Reservoir Design by Hybrid ACO-LP Algorithm

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